US 10 Year Treasury Yield - 24th April 2023 | @ 536 Days | Snippet
'B' class signal detected in the US 10 Year Treasury Yield. Running at an average wavelength of 536 days over 8 completed sample iterations since November 2009 and currently hard down
Signal Class & Attributes
Defining characteristics of the component detected over the sample period.
Detected Signal Class: B - learn more
Average Wavelength: 536 Days
Completed Iterations: 8
Time Frequency Analysis
Time frequency charts (learn more) below will typically show the cycle of interest against price, the bandpass output alone and the bandwidth of the component in the time frequency heatmap, framed in white. If a second chart is displayed it will usually show highpassed price with the extracted signal overlaid for visual clarity.
Signal Detail & Targets
Here we give more detail on the signal and our expectations for price, given the detected attributes of the component. In most cases the time target to hold a trade for is more important, given we focus on cycles in financial markets. Forthcoming trough and peak ranges are based upon the frequency modulation in the sample.
Phase: Hard Down / Troughing1
FM: +- 54 Days2
AM: 0.0633
Next Trough Range: May 1st - August 17th 2023
Next Peak Range: January 16th - May 3rd 2024
Sigma-L Recommendation: Early Buy
Time Target: ~ 10th March 2024
DISCLAIMER: This website/newsletter and the charts/projections contained within it are intended for educational purposes only. Results and projections are hypothetical. We accept no liability for any losses incurred as a result of assertions made due to the information contained within Sigma-L. This report is not intended to instruct investment or purchase of any financial instrument, derivative or asset connected to the information conveyed in the report. Trade and invest at your own risk.
Signal Phase: This is ‘how far along’ the cycle is in it’s period at nowtime and is related to the predicted price action direction.
Signal Frequency Modulation: This is how much, on average, the signal detected varies in frequency (or wavelength) over the whole sample. A lower variance is better and implies better profitability for the component. Frequency modulates relatively slowly over several iterations usually.
Signal Amplitude Modulation: This is how much the component gains or loses power (price influence) across the sample, on average. Amplitude modulation can happen quite quickly and certainly is more evident than frequency modulation in financial markets. The more stable the modulation the better.